The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity d...The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.展开更多
This paper presents an analysis of four open-source Global Digital Elevation Models (GDEMs) and compares them on two topographic profiles (nearly flat, and hills regions) for mapping and geomatics applications. The ch...This paper presents an analysis of four open-source Global Digital Elevation Models (GDEMs) and compares them on two topographic profiles (nearly flat, and hills regions) for mapping and geomatics applications. The chief intention is to investigate if GDEMs-based heights, contour intervals, slopes, and topographic profiles are valid for all map scales of topographic mapping, which constitutes a major issue in mapping activities. Two case studies, the Nile delta in Egypt and Makkah city in Saudi Arabia, have been utilized to represent flat and moderate-topography patterns. The investigated GDEMs include the most-recent released models: ASTER v.3, ACE 2, SRTMGL1 v.3, and NASADEM_HGT v.1 released in 2019 and 2020 with spatial resolutions of 1 and 3 arc seconds. Available accurate Ground Control Points (GCP) consist of 540 stations in the Nile delta and 175 stations in Makkah. Based on the available datasets in two study areas, it has been found that the accuracy of investigated GDEMs over known checkpoints ranges from ±2.5 and ±5.1 meters in the Nile delta region, while it varies between ±5.1 and ±8.0 meters in the Makkah area. That indicates that the utilization of GDEMs in topographic mapping differs significantly between flat and hilly spatial regions. Therefore, it is recommended to avoid using GDEMs for developing topographic maps of scale 1:25,000 or larger in flat regions and map scale 1:50,000 or larger in hilly regions. Additionally, the accomplished results showed that all GDEM-based slopes do not match with the actual slopes from known GCP over cross section’s length up to 30 kilometers. Thus, it is concluded that GDEMs are not the appropriate heights’ source for topographic mapping at medium and large map scales, and could not be utilized for topographic profiling in precise engineering and geomatics applications.展开更多
This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou Ci...This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.展开更多
Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from i...Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.展开更多
Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional meth...Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional methods because of the low accessibility of wetlands, hence remote sensing data have become one of the primary data sources in wetland research. This paper presents a case study conducted at the core area of Honghe National Nature Reserve in the Sanjiang Plain, Northeast China. In this study, three images generated by airship, from Thematic Mapper and from SPOT 5 were selected to produce wetland maps at three different wetland landscape levels. After assessing classification accuracies of the three maps, we compared the different wetland mapping results of 11 plant communities to the airship image, 6 plant ecotypes to the TM image and 9 landscape classifications to the SPOT 5 image. We discussed the different characteristics of the hierarchical ecosystem classifications based on the spatial scales of the different images. The results indicate that spatial scales of remote sensing data have an important link to the hierarchies of wetland plant ecosystems displayed on the wetland landscape maps. The richness of wetland landscape information derived from an image closely relates to its spatial resolution. This study can enrich the ecological classification methods and mapping techniques dealing with the spatial scales of different remote sensing images. With a better understanding of classification accuracies in mapping wetlands by using different scales of remote sensing data, we can make an appropriate approach for dealing with the scale issue of remote sensing images.展开更多
Studies on susceptibility to debris flows at regional scale(100-1000 km^2) are important for the protection and management of mountain areas. To reach this objective, routing models, mainly based on land topography, c...Studies on susceptibility to debris flows at regional scale(100-1000 km^2) are important for the protection and management of mountain areas. To reach this objective, routing models, mainly based on land topography, can be used to predict susceptible areas rapidly while necessitating few input data. In this research, Flow-R model is implemented to create the susceptibility map for the debris flow of the Vizze Valley(BZ, North-Eastern Italy; 134 km^2). The analysis considers the model application at local scale for three sub-catchments and then it explores the model upscaling at the regional scale by verifying two methods to generate the source areas of debris-flow initiation. Using data of an extreme event occurred in the Vizze Valley(4 August 2012) and historical information, the modeling verification highlights that the propagation parameters are relatively simple to set in order to obtain correct runout distances. A double DTM filtering-using a threshold for the upslope contributing area(0.1 km^2) and a threshold for the terrain-slope angle(15°)-provides a satisfactory prediction of source areas and susceptibility map within the geological conditions of the Vizze Valley.展开更多
This paper makes astudy on the interactive digital gener-alization, where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure, which are done by human andcomputer, respec...This paper makes astudy on the interactive digital gener-alization, where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure, which are done by human andcomputer, respectively. And an inter-active map generalization environmentfor large scale topographic map is thendesigned and realized. This researchfocuses on: ① the significance of re-searching an interactive map generali-zation environment, ② the features oflarge scale topographic map and inter-active map generalization, ③ the con-struction of map generalization-orien-ted database platform.展开更多
Soil phosphorus (P) plays a vital role in both ecological and agricultural ecosystems, where total P (TP) in soil serves as a crucial indicator of soil fertility and quality. Most of the studies covered in the literat...Soil phosphorus (P) plays a vital role in both ecological and agricultural ecosystems, where total P (TP) in soil serves as a crucial indicator of soil fertility and quality. Most of the studies covered in the literature employ a single or narrow range of soil databases, which largely overlooks the impact of utilizing multiple mapping scales in estimating soil TP, especially in hilly topographies. In this study, Fujian Province, a subtropical hilly region along China’s southeast coast covered by a complex topographic environment, was taken as a case study. The influence of the mapping scale on soil TP storage (TPS)estimation was analyzed using six digital soil databases that were derived from 3 082 unique soil profiles at different mapping scales, i.e., 1:50 000 (S5),1:200 000 (S20), 1:500 000 (S50), 1:1 000 000 (S100), 1:4 000 000 (S400), and 1:10 000 000 (S1000). The regional TPS in the surface soil (0–20 cm) based on the S5, S20, S50, S100, S400, and S1000 soil maps was 20.72, 22.17, 23.06, 23.05, 22.04, and 23.48 Tg, respectively, and the corresponding TPS at0–100 cm soil depth was 80.98, 80.71, 85.00, 84.03, 82.96, and 86.72 Tg, respectively. By comparing soil TPS in the S20 to S1000 maps to that in the S5map, the relative deviations were 6.37%–13.32%for 0–20 cm and 0.33%–7.09%for 0–100 cm. Moreover, since the S20 map had the lowest relative deviation among different mapping scales as compared to S5, it could provide additional soil information and a richer soil environment than other smaller mapping scales. Our results also revealed that many uncertainties in soil TPS estimation originated from the lack of detailed soil information, i.e., representation and spatial variations among different soil types. From the time and labor perspectives, our work provides useful guidelines to identify the appropriate mapping scale for estimating regional soil TPS in areas like Fujian Province in subtropical China or other places with similar complex topographies. Moreover, it is of tremendous importance to accurately estimate soil TPS to ensure ecosystem stability and sustainable agricultural development, especially for regional decision-making and management of phosphate fertilizer application amounts.展开更多
基金funded by the Natural Science Foundation Committee,China(41364001,41371435)
文摘The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.
文摘This paper presents an analysis of four open-source Global Digital Elevation Models (GDEMs) and compares them on two topographic profiles (nearly flat, and hills regions) for mapping and geomatics applications. The chief intention is to investigate if GDEMs-based heights, contour intervals, slopes, and topographic profiles are valid for all map scales of topographic mapping, which constitutes a major issue in mapping activities. Two case studies, the Nile delta in Egypt and Makkah city in Saudi Arabia, have been utilized to represent flat and moderate-topography patterns. The investigated GDEMs include the most-recent released models: ASTER v.3, ACE 2, SRTMGL1 v.3, and NASADEM_HGT v.1 released in 2019 and 2020 with spatial resolutions of 1 and 3 arc seconds. Available accurate Ground Control Points (GCP) consist of 540 stations in the Nile delta and 175 stations in Makkah. Based on the available datasets in two study areas, it has been found that the accuracy of investigated GDEMs over known checkpoints ranges from ±2.5 and ±5.1 meters in the Nile delta region, while it varies between ±5.1 and ±8.0 meters in the Makkah area. That indicates that the utilization of GDEMs in topographic mapping differs significantly between flat and hilly spatial regions. Therefore, it is recommended to avoid using GDEMs for developing topographic maps of scale 1:25,000 or larger in flat regions and map scale 1:50,000 or larger in hilly regions. Additionally, the accomplished results showed that all GDEM-based slopes do not match with the actual slopes from known GCP over cross section’s length up to 30 kilometers. Thus, it is concluded that GDEMs are not the appropriate heights’ source for topographic mapping at medium and large map scales, and could not be utilized for topographic profiling in precise engineering and geomatics applications.
基金the Natural Science Foundation of China(41807285)Interdisciplinary Innovation Fund of Natural Science,NanChang University(9167-28220007-YB2107).
文摘This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.
文摘Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.
基金Under the auspices of National Natural Science Foundation of China (No. 40871241, 40771170)National High Technology Research and Development Program of China (No. 2007AA12Z176)
文摘Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional methods because of the low accessibility of wetlands, hence remote sensing data have become one of the primary data sources in wetland research. This paper presents a case study conducted at the core area of Honghe National Nature Reserve in the Sanjiang Plain, Northeast China. In this study, three images generated by airship, from Thematic Mapper and from SPOT 5 were selected to produce wetland maps at three different wetland landscape levels. After assessing classification accuracies of the three maps, we compared the different wetland mapping results of 11 plant communities to the airship image, 6 plant ecotypes to the TM image and 9 landscape classifications to the SPOT 5 image. We discussed the different characteristics of the hierarchical ecosystem classifications based on the spatial scales of the different images. The results indicate that spatial scales of remote sensing data have an important link to the hierarchies of wetland plant ecosystems displayed on the wetland landscape maps. The richness of wetland landscape information derived from an image closely relates to its spatial resolution. This study can enrich the ecological classification methods and mapping techniques dealing with the spatial scales of different remote sensing images. With a better understanding of classification accuracies in mapping wetlands by using different scales of remote sensing data, we can make an appropriate approach for dealing with the scale issue of remote sensing images.
基金granted by the Junior Research Grant Universitàdegli Studi di Padova,year 2013,prot.CPDR138494(“Criticitàidrauliche nel reticolo montano nei riguardi del movimento di detrito legnoso e di colate detritiche”Prof.Vincenzo D’Agostino)
文摘Studies on susceptibility to debris flows at regional scale(100-1000 km^2) are important for the protection and management of mountain areas. To reach this objective, routing models, mainly based on land topography, can be used to predict susceptible areas rapidly while necessitating few input data. In this research, Flow-R model is implemented to create the susceptibility map for the debris flow of the Vizze Valley(BZ, North-Eastern Italy; 134 km^2). The analysis considers the model application at local scale for three sub-catchments and then it explores the model upscaling at the regional scale by verifying two methods to generate the source areas of debris-flow initiation. Using data of an extreme event occurred in the Vizze Valley(4 August 2012) and historical information, the modeling verification highlights that the propagation parameters are relatively simple to set in order to obtain correct runout distances. A double DTM filtering-using a threshold for the upslope contributing area(0.1 km^2) and a threshold for the terrain-slope angle(15°)-provides a satisfactory prediction of source areas and susceptibility map within the geological conditions of the Vizze Valley.
基金The project supported by the Key Program of National Natural Science Foundation of China under Grant No. 70431002 and National Natural Science Foundation of China under Grant Nos. 70371068 and 10247005 The authors thank Drs. Atay and Chun-Guang Li for their useful advices and discussions.
文摘在纸,我们学习效果没有规模(SF ) 在联合地图格子(电流型逻辑) 的动态同步和控制上的拓扑学。我们的策略是使用三个反馈控制方法,包括经常的反馈和推迟时间的反馈的二种类型,到到达需要的同步状态的网络节点的小部分。二控制分叉图诗句反馈力量分别地被获得。当£线性地被增加,为第一推迟时间的反馈控制的批评反馈力量γ _ c 的值线性地被增加,这被发现。有 SF 的电流型逻辑失去同步,如果γ 】
γ _ c.Numerical 例子被举表明所有结果, intermittency 发生。
文摘This paper makes astudy on the interactive digital gener-alization, where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure, which are done by human andcomputer, respectively. And an inter-active map generalization environmentfor large scale topographic map is thendesigned and realized. This researchfocuses on: ① the significance of re-searching an interactive map generali-zation environment, ② the features oflarge scale topographic map and inter-active map generalization, ③ the con-struction of map generalization-orien-ted database platform.
基金国家重点基础研究发展规划(973)(the National Grand Fundamental Research 973 Program of China under Grant No.2002CB312103)河南省自然科学基金(the Natural Science Foundation of Henan Province of China under Grant No.0611051900)。
基金supported by the National Natural Science Foundation of China(Nos.41971050 and 42207271)the Provincial Natural Science Foundation of Fujian,China(No.2022J05036)the Open Project Program of the State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry,Institute of Atmospheric Physics,Chinese Academy of Sciences(No.LAPC-KF-2022-08)。
文摘Soil phosphorus (P) plays a vital role in both ecological and agricultural ecosystems, where total P (TP) in soil serves as a crucial indicator of soil fertility and quality. Most of the studies covered in the literature employ a single or narrow range of soil databases, which largely overlooks the impact of utilizing multiple mapping scales in estimating soil TP, especially in hilly topographies. In this study, Fujian Province, a subtropical hilly region along China’s southeast coast covered by a complex topographic environment, was taken as a case study. The influence of the mapping scale on soil TP storage (TPS)estimation was analyzed using six digital soil databases that were derived from 3 082 unique soil profiles at different mapping scales, i.e., 1:50 000 (S5),1:200 000 (S20), 1:500 000 (S50), 1:1 000 000 (S100), 1:4 000 000 (S400), and 1:10 000 000 (S1000). The regional TPS in the surface soil (0–20 cm) based on the S5, S20, S50, S100, S400, and S1000 soil maps was 20.72, 22.17, 23.06, 23.05, 22.04, and 23.48 Tg, respectively, and the corresponding TPS at0–100 cm soil depth was 80.98, 80.71, 85.00, 84.03, 82.96, and 86.72 Tg, respectively. By comparing soil TPS in the S20 to S1000 maps to that in the S5map, the relative deviations were 6.37%–13.32%for 0–20 cm and 0.33%–7.09%for 0–100 cm. Moreover, since the S20 map had the lowest relative deviation among different mapping scales as compared to S5, it could provide additional soil information and a richer soil environment than other smaller mapping scales. Our results also revealed that many uncertainties in soil TPS estimation originated from the lack of detailed soil information, i.e., representation and spatial variations among different soil types. From the time and labor perspectives, our work provides useful guidelines to identify the appropriate mapping scale for estimating regional soil TPS in areas like Fujian Province in subtropical China or other places with similar complex topographies. Moreover, it is of tremendous importance to accurately estimate soil TPS to ensure ecosystem stability and sustainable agricultural development, especially for regional decision-making and management of phosphate fertilizer application amounts.